Merge pull request #51 from fbcotter/py3support

Py3support

evaluate.py

@@ -4,7 +4,7 @@
 import transform, numpy as np, vgg, pdb, os
 import scipy.misc
 import tensorflow as tf
-from utils import save_img, get_img, exists, list_files, check_version
+from utils import save_img, get_img, exists, list_files
 from argparse import ArgumentParser
 from collections import defaultdict
 import time
@@ -238,7 +238,6 @@ def check_opts(opts):
         assert opts.batch_size > 0
 
 def main():
-    check_version()
     parser = build_parser()
     opts = parser.parse_args()
     check_opts(opts)
@@ -254,8 +253,8 @@ def main():
                     device=opts.device)
     else:
         files = list_files(opts.in_path)
-        full_in = map(lambda x: os.path.join(opts.in_path,x), files)
-        full_out = map(lambda x: os.path.join(opts.out_path,x), files)
+        full_in = [os.path.join(opts.in_path,x) for x in files]
+        full_out = [os.path.join(opts.out_path,x) for x in files]
         if opts.allow_different_dimensions:
             ffwd_different_dimensions(full_in, full_out, opts.checkpoint_dir, 
                     device_t=opts.device, batch_size=opts.batch_size)

setup.sh

@@ -1,3 +1,5 @@
+#! /bin/bash
+
 mkdir data
 cd data
 wget http://www.vlfeat.org/matconvnet/models/beta16/imagenet-vgg-verydeep-19.mat

src/optimize.py

@@ -1,4 +1,5 @@
 from __future__ import print_function
+import functools
 import vgg, pdb, time
 import tensorflow as tf, numpy as np, os
 import transform
@@ -75,7 +76,7 @@ def optimize(content_targets, style_target, content_weight, style_weight,
             style_gram = style_features[style_layer]
             style_losses.append(2 * tf.nn.l2_loss(grams - style_gram)/style_gram.size)
 
-        style_loss = style_weight * reduce(tf.add, style_losses) / batch_size
+        style_loss = style_weight * functools.reduce(tf.add, style_losses) / batch_size
 
         # total variation denoising
         tv_y_size = _tensor_size(preds[:,1:,:,:])
@@ -138,4 +139,4 @@ def optimize(content_targets, style_target, content_weight, style_weight,
 
 def _tensor_size(tensor):
     from operator import mul
-    return reduce(mul, (d.value for d in tensor.get_shape()[1:]), 1)
+    return functools.reduce(mul, (d.value for d in tensor.get_shape()[1:]), 1)

src/utils.py

@@ -31,13 +31,3 @@ def list_files(in_path):
 
     return files
 
-def check_version():
-    if sys.version_info[0] != 2:
-        err_str = (
-            "This project only supports Python 2! Either run using "
-            "Python 2 or submit a pull request to "
-            "https://github.com/lengstrom/fast-style-transfer/ "
-            "to make the project version neutral!"
-        )
-
-        raise Exception(err_str)

style.py

@@ -4,7 +4,7 @@
 import numpy as np, scipy.misc 
 from optimize import optimize
 from argparse import ArgumentParser
-from utils import save_img, get_img, exists, list_files, check_version
+from utils import save_img, get_img, exists, list_files
 import evaluate
 
 CONTENT_WEIGHT = 7.5e0
@@ -106,10 +106,10 @@ def check_opts(opts):
 
 def _get_files(img_dir):
     files = list_files(img_dir)
-    return map(lambda x: os.path.join(img_dir,x), files)
+    return [os.path.join(img_dir,x) for x in files]
+
 
 def main():
-    check_version()
     parser = build_parser()
     options = parser.parse_args()
     check_opts(options)

transform_video.py

@@ -67,8 +67,8 @@ def main():
 
         subprocess.call(" ".join(in_args), shell=True)
         base_names = list_files(in_dir)
-        in_files = list(map(lambda x: os.path.join(in_dir, x), base_names))
-        out_files = list(map(lambda x: os.path.join(out_dir, x), base_names))
+        in_files = [os.path.join(in_dir, x) for x in base_names]
+        out_files = [os.path.join(out_dir, x) for x in base_names]
         evaluate.ffwd(in_files, out_files, opts.checkpoint, device_t=opts.device,
                       batch_size=opts.batch_size)
         fr = 30 # wtf